### Abstract

A string barcoding problem is defined as to find a minimum set of substrings that distinguish between all strings in a given set of strings . In a biological sense the given strings represent a set of genomic sequences and the substrings serve as probes in a hybridisation experiment. In this paper, we study a variant of the string barcoding problem in which the substrings have to be chosen from a particular set of substrings of cardinality n. This variant can be also obtained from more general test set problem, see, e.g., [1] by fixing appropriate parameters. We present almost optimal -time approximation algorithm for the considered problem. Our approximation procedure is a modification of the algorithm due to Berman et al. [1] which obtains the best possible approximation ratio (1∈+∈ln n), providing . The improved time complexity is a direct consequence of more careful management of processed sets, use of several specialised graph and string data structures as well as tighter time complexity analysis based on an amortised argument.

Original language | English (US) |
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Title of host publication | Combinatorial Pattern Matching - 19th Annual Symposium, CPM 2008, Proceedings |

Pages | 82-94 |

Number of pages | 13 |

DOIs | |

State | Published - Jul 1 2008 |

Externally published | Yes |

Event | 19th Annual Symposium on Combinatorial Pattern Matching, CPM 2008 - Pisa, Italy Duration: Jun 18 2008 → Jun 20 2008 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 5029 LNCS |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Conference

Conference | 19th Annual Symposium on Combinatorial Pattern Matching, CPM 2008 |
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Country | Italy |

City | Pisa |

Period | 6/18/08 → 6/20/08 |

### Fingerprint

### ASJC Scopus subject areas

- Theoretical Computer Science
- Computer Science(all)

### Cite this

*Combinatorial Pattern Matching - 19th Annual Symposium, CPM 2008, Proceedings*(pp. 82-94). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5029 LNCS). https://doi.org/10.1007/978-3-540-69068-9_10